
@article{oakden2019hidden,
  title={Hidden stratification causes clinically meaningful failures in machine learning for medical imaging},
  author={Oakden-Rayner, Luke and Dunnmon, Jared and Carneiro, Gustavo and R{\'e}, Christopher},
  journal={arXiv preprint arXiv:1909.12475},
  year={2019}
}

@inproceedings{liu2015deep,
  title={Deep learning face attributes in the wild},
  author={Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={3730--3738},
  year={2015}
}

@inproceedings{sagawa2020distributionally,
  title={Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization},
  author={Sagawa, Shiori and Koh, Pang Wei and Hashimoto, Tatsunori B and Liang, Percy},
  booktitle={The International Conference on Learning Representations ({ICLR})},
  year={2020}
}


@inproceedings{zhu2017unpaired,
  title={Unpaired image-to-image translation using cycle-consistent adversarial networks},
  author={Zhu, Jun-Yan and Park, Taesung and Isola, Phillip and Efros, Alexei A},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={2223--2232},
  year={2017}
}

@article{mariani2018bagan,
  title={Bagan: Data augmentation with balancing gan},
  author={Mariani, Giovanni and Scheidegger, Florian and Istrate, Roxana and Bekas, Costas and Malossi, Cristiano},
  journal={arXiv preprint arXiv:1803.09655},
  year={2018}
}

@article{zhang2017mixup,
  title={mixup: Beyond empirical risk minimization},
  author={Zhang, Hongyi and Cisse, Moustapha and Dauphin, Yann N and Lopez-Paz, David},
  journal={arXiv preprint arXiv:1710.09412},
  year={2017}
}

@article{cubuk2019randaugment,
  title={RandAugment: Practical data augmentation with no separate search},
  author={Cubuk, Ekin D and Zoph, Barret and Shlens, Jonathon and Le, Quoc V},
  journal={arXiv preprint arXiv:1909.13719},
  year={2019}
}

@inproceedings{yin2019fourier,
  title={A fourier perspective on model robustness in computer vision},
  author={Yin, Dong and Lopes, Raphael Gontijo and Shlens, Jon and Cubuk, Ekin Dogus and Gilmer, Justin},
  booktitle={Advances in Neural Information Processing Systems},
  pages={13255--13265},
  year={2019}
}

@inproceedings{li2018deep,
  title={Deep domain generalization via conditional invariant adversarial networks},
  author={Li, Ya and Tian, Xinmei and Gong, Mingming and Liu, Yajing and Liu, Tongliang and Zhang, Kun and Tao, Dacheng},
  booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
  pages={624--639},
  year={2018}
}

@article{simon1954spurious,
  title={Spurious correlation: A causal interpretation},
  author={Simon, Herbert A},
  journal={Journal of the American statistical Association},
  volume={49},
  number={267},
  pages={467--479},
  year={1954},
  publisher={Taylor \& Francis}
}

@inproceedings{buolamwini2018gender,
  title={Gender shades: Intersectional accuracy disparities in commercial gender classification},
  author={Buolamwini, Joy and Gebru, Timnit},
  booktitle={Conference on fairness, accountability and transparency},
  pages={77--91},
  year={2018}
}

@article{wah2011caltech,
  title={The caltech-ucsd birds-200-2011 dataset},
  author={Wah, Catherine and Branson, Steve and Welinder, Peter and Perona, Pietro and Belongie, Serge},
  year={2011},
  publisher={California Institute of Technology}
}

@inproceedings{codella2018skin,
  title={Skin lesion analysis toward melanoma detection: A challenge at the 2017 international symposium on biomedical imaging (isbi), hosted by the international skin imaging collaboration (isic)},
  author={Codella, Noel CF and Gutman, David and Celebi, M Emre and Helba, Brian and Marchetti, Michael A and Dusza, Stephen W and Kalloo, Aadi and Liopyris, Konstantinos and Mishra, Nabin and Kittler, Harald and others},
  booktitle={2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)},
  pages={168--172},
  year={2018},
  organization={IEEE}
}

@article{ho2019population,
  title={Population based augmentation: Efficient learning of augmentation policy schedules},
  author={Ho, Daniel and Liang, Eric and Stoica, Ion and Abbeel, Pieter and Chen, Xi},
  journal={arXiv preprint arXiv:1905.05393},
  year={2019}
}

@article{ganin2016domain,
  title={Domain-adversarial training of neural networks},
  author={Ganin, Yaroslav and Ustinova, Evgeniya and Ajakan, Hana and Germain, Pascal and Larochelle, Hugo and Laviolette, Fran{\c{c}}ois and Marchand, Mario and Lempitsky, Victor},
  journal={The Journal of Machine Learning Research},
  volume={17},
  number={1},
  pages={2096--2030},
  year={2016},
  publisher={JMLR.org}
}

@inproceedings{long2018conditional,
  title={Conditional adversarial domain adaptation},
  author={Long, Mingsheng and Cao, Zhangjie and Wang, Jianmin and Jordan, Michael I},
  booktitle={Advances in Neural Information Processing Systems},
  pages={1640--1650},
  year={2018}
}


@article{devries2017improved,
  title={Improved regularization of convolutional neural networks with cutout},
  author={DeVries, Terrance and Taylor, Graham W},
  journal={arXiv preprint arXiv:1708.04552},
  year={2017}
}

@article{lecun1998gradient,
  title={Gradient-based learning applied to document recognition},
  author={LeCun, Yann and Bottou, L{\'e}on and Bengio, Yoshua and Haffner, Patrick},
  journal={Proceedings of the IEEE},
  volume={86},
  number={11},
  pages={2278--2324},
  year={1998},
  publisher={Ieee}
}

@article{mu2019mnist,
  title={Mnist-c: A robustness benchmark for computer vision},
  author={Mu, Norman and Gilmer, Justin},
  journal={arXiv preprint arXiv:1906.02337},
  year={2019}
}

@inproceedings{he2016identity,
  title={Identity mappings in deep residual networks},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={European conference on computer vision},
  pages={630--645},
  year={2016},
  organization={Springer}
}

%%% DATA AUGMENTATION

@inproceedings{ratner2017learning,
  title={Learning to compose domain-specific transformations for data augmentation},
  author={Ratner, Alexander J and Ehrenberg, Henry and Hussain, Zeshan and Dunnmon, Jared and R{\'e}, Christopher},
  booktitle={Advances in neural information processing systems},
  pages={3236--3246},
  year={2017}
}
@article{hendrycks2019augmix,
  title={AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty},
  author={Hendrycks, Dan and Mu, Norman and Cubuk, Ekin D and Zoph, Barret and Gilmer, Justin and Lakshminarayanan, Balaji},
  journal={arXiv preprint arXiv:1912.02781},
  year={2019}
}

@inproceedings{cubuk2019autoaugment,
  title={Autoaugment: Learning augmentation strategies from data},
  author={Cubuk, Ekin D and Zoph, Barret and Mane, Dandelion and Vasudevan, Vijay and Le, Quoc V},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={113--123},
  year={2019}
}

@inproceedings{lim2019fast,
  title={Fast autoaugment},
  author={Lim, Sungbin and Kim, Ildoo and Kim, Taesup and Kim, Chiheon and Kim, Sungwoong},
  booktitle={Advances in Neural Information Processing Systems},
  pages={6662--6672},
  year={2019}
}


@inproceedings{yun2019cutmix,
  title={Cutmix: Regularization strategy to train strong classifiers with localizable features},
  author={Yun, Sangdoo and Han, Dongyoon and Oh, Seong Joon and Chun, Sanghyuk and Choe, Junsuk and Yoo, Youngjoon},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
  pages={6023--6032},
  year={2019}
}


@inproceedings{berthelot2019mixmatch,
  title={Mixmatch: A holistic approach to semi-supervised learning},
  author={Berthelot, David and Carlini, Nicholas and Goodfellow, Ian and Papernot, Nicolas and Oliver, Avital and Raffel, Colin A},
  booktitle={Advances in Neural Information Processing Systems},
  pages={5050--5060},
  year={2019}
}

@inproceedings{upchurch2017deep,
  title={Deep feature interpolation for image content changes},
  author={Upchurch, Paul and Gardner, Jacob and Pleiss, Geoff and Pless, Robert and Snavely, Noah and Bala, Kavita and Weinberger, Kilian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={7064--7073},
  year={2017}
}

%%%% GANs

@inproceedings{choi2018stargan,
  title={Stargan: Unified generative adversarial networks for multi-domain image-to-image translation},
  author={Choi, Yunjey and Choi, Minje and Kim, Munyoung and Ha, Jung-Woo and Kim, Sunghun and Choo, Jaegul},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={8789--8797},
  year={2018}
}

@article{almahairi2018augmented,
  title={Augmented cyclegan: Learning many-to-many mappings from unpaired data},
  author={Almahairi, Amjad and Rajeswar, Sai and Sordoni, Alessandro and Bachman, Philip and Courville, Aaron},
  journal={arXiv preprint arXiv:1802.10151},
  year={2018}
}

@article{antoniou2017data,
  title={Data augmentation generative adversarial networks},
  author={Antoniou, Antreas and Storkey, Amos and Edwards, Harrison},
  journal={arXiv preprint arXiv:1711.04340},
  year={2017}
}

@article{gowal2019achieving,
  title={Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations},
  author={Gowal, Sven and Qin, Chongli and Huang, Po-Sen and Cemgil, Taylan and Dvijotham, Krishnamurthy and Mann, Timothy and Kohli, Pushmeet},
  journal={arXiv preprint arXiv:1912.03192},
  year={2019}
}

@article{kannan2018adversarial,
  title={Adversarial logit pairing},
  author={Kannan, Harini and Kurakin, Alexey and Goodfellow, Ian},
  journal={arXiv preprint arXiv:1803.06373},
  year={2018}
}

@inproceedings{zheng2016improving,
  title={Improving the robustness of deep neural networks via stability training},
  author={Zheng, Stephan and Song, Yang and Leung, Thomas and Goodfellow, Ian},
  booktitle={Proceedings of the ieee conference on computer vision and pattern recognition},
  pages={4480--4488},
  year={2016}
}

@article{xie2019unsupervised,
  title={Unsupervised data augmentation for consistency training},
  author={Xie, Qizhe and Dai, Zihang and Hovy, Eduard and Luong, Minh-Thang and Le, Quoc V},
  journal={arXiv preprint arXiv:1904.12848},
  year={2019}
}

@inproceedings{isola2017image,
  title={Image-to-image translation with conditional adversarial networks},
  author={Isola, Phillip and Zhu, Jun-Yan and Zhou, Tinghui and Efros, Alexei A},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={1125--1134},
  year={2017}
}

@article{heinze2017conditional,
  title={Conditional variance penalties and domain shift robustness},
  author={Heinze-Deml, Christina and Meinshausen, Nicolai},
  journal={arXiv preprint arXiv:1710.11469},
  year={2017}
}

@article{winkler2019association,
  title={Association between surgical skin markings in dermoscopic images and diagnostic performance of a deep learning convolutional neural network for melanoma recognition},
  author={Winkler, Julia K and Fink, Christine and Toberer, Ferdinand and Enk, Alexander and Deinlein, Teresa and Hofmann-Wellenhof, Rainer and Thomas, Luc and Lallas, Aimilios and Blum, Andreas and Stolz, Wilhelm and others},
  journal={JAMA dermatology},
  volume={155},
  number={10},
  pages={1135--1141},
  year={2019},
  publisher={American Medical Association}
}

@inproceedings{selvaraju2017grad,
  title={Grad-cam: Visual explanations from deep networks via gradient-based localization},
  author={Selvaraju, Ramprasaath R and Cogswell, Michael and Das, Abhishek and Vedantam, Ramakrishna and Parikh, Devi and Batra, Dhruv},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={618--626},
  year={2017}
}

@article{grover2019alignflow,
  title={AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows},
  author={Grover, Aditya and Chute, Christopher and Shu, Rui and Cao, Zhangjie and Ermon, Stefano},
  journal={arXiv preprint arXiv:1905.12892},
  year={2019}
}

@article{Ratner2017LearningTC,
  title={Learning to Compose Domain-Specific Transformations for Data Augmentation},
  author={Alexander J. Ratner and Henry R. Ehrenberg and Zeshan Hussain and Jared Dunnmon and Christopher R{\'e}},
  journal={Advances in neural information processing systems},
  year={2017},
  volume={30},
  pages={
          3239-3249
        }
}

@inproceedings{gan,
  title={Generative adversarial nets},
  author={Goodfellow, Ian and Pouget-Abadie, Jean and Mirza, Mehdi and Xu, Bing and Warde-Farley, David and Ozair, Sherjil and Courville, Aaron and Bengio, Yoshua},
  booktitle={Advances in neural information processing systems},
  pages={2672--2680},
  year={2014}
}

@article{Dao2018AKT,
  title={A Kernel Theory of Modern Data Augmentation},
  author={Tri Dao and Albert Gu and Alexander J. Ratner and Virginia Smith and Christopher De Sa and Christopher R{\'e}},
  journal={Proceedings of machine learning research},
  year={2018},
  volume={97},
  pages={
          1528-1537
        }
}

@article{archambault2019mixup,
  title={MixUp as Directional Adversarial Training},
  author={Archambault, Guillaume P and Mao, Yongyi and Guo, Hongyu and Zhang, Richong},
  journal={arXiv preprint arXiv:1906.06875},
  year={2019}
}

@inproceedings{dwibedi2017cut,
  title={Cut, paste and learn: Surprisingly easy synthesis for instance detection},
  author={Dwibedi, Debidatta and Misra, Ishan and Hebert, Martial},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
  pages={1301--1310},
  year={2017}
}

@article{Zoph2019LearningDA,
  title={Learning Data Augmentation Strategies for Object Detection},
  author={Barret Zoph and Ekin Dogus Cubuk and Golnaz Ghiasi and Tsung-Yi Lin and Jonathon Shlens and Quoc V. Le},
  journal={ArXiv},
  year={2019},
  volume={abs/1906.11172}
}

@article{Dvornik2018OnTI,
  title={On the Importance of Visual Context for Data Augmentation in Scene Understanding},
  author={Nikita Dvornik and Julien Mairal and Cordelia Schmid},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  year={2018}
}

@inproceedings{Wei2019EDAED,
  title={EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks},
  author={Jason Wei and Kai Zou},
  booktitle={EMNLP/IJCNLP},
  year={2019}
}

@inproceedings{Simard1998TransformationII,
  title={Transformation Invariance in Pattern Recognition - Tangent Distance and Tangent Propagation},
  author={Patrice Y. Simard and Yann LeCun and John S. Denker and Bernard Victorri},
  booktitle={Neural Networks: Tricks of the Trade},
  year={1998}
}

@article{Szegedy2014GoingDW,
  title={Going deeper with convolutions},
  author={Christian Szegedy and Wei Liu and Yangqing Jia and Pierre Sermanet and Scott Reed and Dragomir Anguelov and Dumitru Erhan and Vincent Vanhoucke and Andrew Rabinovich},
  journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2014},
  pages={1-9}
}

@inproceedings{Krizhevsky2012ImageNetCW,
  title={ImageNet Classification with Deep Convolutional Neural Networks},
  author={Alex Krizhevsky and Ilya Sutskever and Geoffrey E. Hinton},
  booktitle={NIPS},
  year={2012}
}

@article{Cui2015DataAF,
  title={Data Augmentation for Deep Neural Network Acoustic Modeling},
  author={Xiaodong Cui and Vaibhava Goel and Brian Kingsbury},
  journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
  year={2015},
  volume={23},
  pages={1469-1477}
}

@inproceedings{Ko2015AudioAF,
  title={Audio augmentation for speech recognition},
  author={Tom Ko and Vijayaditya Peddinti and Daniel Povey and Sanjeev Khudanpur},
  booktitle={INTERSPEECH},
  year={2015}
}

@inproceedings{Kolomiyets2011ModelPortabilityEF,
  title={Model-Portability Experiments for Textual Temporal Analysis},
  author={Oleksandr Kolomiyets and Steven Bethard and Marie-Francine Moens},
  booktitle={ACL},
  year={2011}
}

@inproceedings{Zhang2015CharacterlevelCN,
  title={Character-level Convolutional Networks for Text Classification},
  author={Xiang Zhang and Junbo Jake Zhao and Yann LeCun},
  booktitle={NIPS},
  year={2015}
}

@inproceedings{Wang2015ThatsSA,
  title={That's So Annoying!!!: A Lexical and Frame-Semantic Embedding Based Data Augmentation Approach to Automatic Categorization of Annoying Behaviors using petpeeve Tweets},
  author={William Yang Wang and Diyi Yang},
  booktitle={EMNLP},
  year={2015}
}

@article{Yu2018QANetCL,
  title={QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension},
  author={Adams Wei Yu and David Dohan and Minh-Thang Luong and Rui Zhao and Kai Chen and Mohammad Norouzi and Quoc V. Le},
  journal={ArXiv},
  year={2018},
  volume={abs/1804.09541}
}


@article{Xie2017DataNA,
  title={Data Noising as Smoothing in Neural Network Language Models},
  author={Ziang Xie and Sida I. Wang and Jiwei Li and Daniel L{\'e}vy and Aiming Nie and Dan Jurafsky and Andrew Y. Ng},
  journal={ArXiv},
  year={2017},
  volume={abs/1703.02573}
}

@article{Sennrich2015ImprovingNM,
  title={Improving Neural Machine Translation Models with Monolingual Data},
  author={Rico Sennrich and Barry Haddow and Alexandra Birch},
  journal={ArXiv},
  year={2015},
  volume={abs/1511.06709}
}

@inproceedings{Fadaee2017DataAF,
  title={Data Augmentation for Low-Resource Neural Machine Translation},
  author={Marzieh Fadaee and Arianna Bisazza and Christof Monz},
  booktitle={ACL},
  year={2017}
}

@inproceedings{Silfverberg2017DataAF,
  title={Data Augmentation for Morphological Reinflection},
  author={Miikka Silfverberg and Adam Wiemerslage and Ling Liu and Lingshuang Jack Mao},
  booktitle={CoNLL Shared Task},
  year={2017}
}

@inproceedings{Hu2017TowardCG,
  title={Toward Controlled Generation of Text},
  author={Zhiting Hu and Zichao Yang and Xiaodan Liang and Ruslan Salakhutdinov and Eric P. Xing},
  booktitle={ICML},
  year={2017}
}


@article{Simard2003BestPF,
  title={Best practices for convolutional neural networks applied to visual document analysis},
  author={Patrice Y. Simard and David Steinkraus and John C. Platt},
  journal={Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.},
  year={2003},
  pages={958-963}
}

@article{Ciresan2012MulticolumnDN,
  title={Multi-column deep neural networks for image classification},
  author={Dan C. Ciresan and Ueli Meier and J{\"u}rgen Schmidhuber},
  journal={2012 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2012},
  pages={3642-3649}
}

@article{Ciresan2011HighPerformanceNN,
  title={High-Performance Neural Networks for Visual Object Classification},
  author={Dan C. Ciresan and Ueli Meier and Jonathan Masci and Luca Maria Gambardella and J{\"u}rgen Schmidhuber},
  journal={ArXiv},
  year={2011},
  volume={abs/1102.0183}
}


@inproceedings{Yaeger1996EffectiveTO,
  title={Effective Training of a Neural Network Character Classifier for Word Recognition},
  author={Larry S. Yaeger and Richard F. Lyon and Brandyn J. Webb},
  booktitle={NIPS},
  year={1996}
}

@inproceedings{Simard1991TangentP,
  title={Tangent Prop - A Formalism for Specifying Selected Invariances in an Adaptive Network},
  author={Patrice Y. Simard and Bernard Victorri and Yann LeCun and John S. Denker},
  booktitle={NIPS},
  year={1991}
}

@inproceedings{Simard1992EfficientPR,
  title={Efficient Pattern Recognition Using a New Transformation Distance},
  author={Patrice Y. Simard and Yann LeCun and John S. Denker},
  booktitle={NIPS},
  year={1992}
}

@incollection{baird1992document,
  title={Document image defect models},
  author={Baird, Henry S},
  booktitle={Structured Document Image Analysis},
  pages={546--556},
  year={1992},
  publisher={Springer}
}


@article{Kobayashi2018ContextualAD,
  title={Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations},
  author={Sosuke Kobayashi},
  journal={ArXiv},
  year={2018},
  volume={abs/1805.06201}
}

@article{Jia2016DataRF,
  title={Data Recombination for Neural Semantic Parsing},
  author={Robin Jia and Percy Liang},
  journal={ArXiv},
  year={2016},
  volume={abs/1606.03622}
}

@inproceedings{Deschacht2009SemisupervisedSR,
  title={Semi-supervised Semantic Role Labeling Using the Latent Words Language Model},
  author={Koen Deschacht and Marie-Francine Moens},
  booktitle={EMNLP},
  year={2009}
}

@inproceedings{Jaitly2013VocalTL,
  title={Vocal Tract Length Perturbation (VTLP) improves speech recognition},
  author={Navdeep Jaitly and E. S. Hinton},
  booktitle={Proc. ICML Workshop on Deep Learning for Audio, Speech and Language},
  year={2013}
}

@inproceedings{LeCun1998GradientbasedLA,
  title={Gradient-based learning applied to document recognition},
  author={Yann LeCun and L{\'e}on Bottou and Yoshua Bengio and Patrick Haffner},
  year={1998}
}

@article{Stylianou1998ContinuousPT,
  title={Continuous probabilistic transform for voice conversion},
  author={Yannis Stylianou and Olivier Capp{\'e} and Eric Moulines},
  journal={IEEE Trans. Speech and Audio Processing},
  year={1998},
  volume={6},
  pages={131-142}
}

@article{demyanov2015invariant,
	Author = {Demyanov, Sergey and Bailey, James and Kotagiri, Ramamohanarao and Leckie, Christopher},
	Journal = {arXiv:1502.04434},
	Title = {Invariant backpropagation: how to train a transformation-invariant neural network},
	Year = {2015}
}


@article{Karras2018ASG,
  title={A Style-Based Generator Architecture for Generative Adversarial Networks},
  author={Tero Karras and Samuli Laine and Timo Aila},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2018},
  pages={4396-4405}
}

@inproceedings{Mazzone2019ArtCA,
  title={Art, creativity, and the potential of artificial intelligence},
  author={Mazzone, Marian and Elgammal, Ahmed},
  booktitle={Arts},
  volume={8},
  pages={26},
  year={2019},
  organization={Multidisciplinary Digital Publishing Institute}
}


@article{Brock2016NeuralPE,
  title={Neural Photo Editing with Introspective Adversarial Networks},
  author={Andrew Brock and Theodore Lim and James M. Ritchie and Nick Weston},
  journal={ArXiv},
  year={2016},
  volume={abs/1609.07093}
}

@inproceedings{Reed2014LearningTD,
  title={Learning to Disentangle Factors of Variation with Manifold Interaction},
  author={Scott E. Reed and Kihyuk Sohn and Yuting Zhang and Honglak Lee},
  booktitle={ICML},
  year={2014}
}

@inproceedings{Reed2015DeepVA,
  title={Deep Visual Analogy-Making},
  author={Scott E. Reed and Yi Zhang and Yuting Zhang and Honglak Lee},
  booktitle={NIPS},
  year={2015}
}

@article{Gardner2015DeepMT,
  title={Deep Manifold Traversal: Changing Labels with Convolutional Features},
  author={Jacob R. Gardner and Matt J. Kusner and Yixuan Li and Paul Upchurch and Kilian Q. Weinberger and John E. Hopcroft},
  journal={ArXiv},
  year={2015},
  volume={abs/1511.06421}
}

@article{Mahendran2014UnderstandingDI,
  title={Understanding deep image representations by inverting them},
  author={Aravindh Mahendran and Andrea Vedaldi},
  journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2014},
  pages={5188-5196}
}

@article{Gatys2015ANA,
  title={A Neural Algorithm of Artistic Style},
  author={Leon A. Gatys and Alexander S. Ecker and Matthias Bethge},
  journal={ArXiv},
  year={2015},
  volume={abs/1508.06576}
}


@article{Garrido2014AutomaticFR,
  title={Automatic Face Reenactment},
  author={Pablo Garrido and Levi Valgaerts and Ole Rehmsen and Thorsten Thorm{\"a}hlen and Patrick P{\'e}rez and Christian Theobalt},
  journal={2014 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2014},
  pages={4217-4224}
}

@inproceedings{Girdhar2016LearningAP,
  title={Learning a Predictable and Generative Vector Representation for Objects},
  author={Rohit Girdhar and David F. Fouhey and Mikel Rodriguez and Abhinav Gupta},
  booktitle={ECCV},
  year={2016}
}

@article{KemelmacherShlizerman2016TransfiguringP,
  title={Transfiguring portraits},
  author={Ira Kemelmacher-Shlizerman},
  journal={ACM Trans. Graph.},
  year={2016},
  volume={35},
  pages={94:1-94:8}
}

@inproceedings{KemelmacherShlizerman2011ExploringP,
  title={Exploring photobios},
  author={Ira Kemelmacher-Shlizerman and Eli Shechtman and Rahul Garg and Steven M. Seitz},
  booktitle={SIGGRAPH 2011},
  year={2011}
}

@article{Thies2015RealtimeET,
  title={Real-time expression transfer for facial reenactment},
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@inproceedings{Sun2019UnlabeledSG,
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@inproceedings{Hu2019LearningDM,
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@article{10.1001/jamadermatol.2018.2348,
    author = {Adamson, Adewole S. and Smith, Avery},
    title = "{Machine Learning and Health Care Disparities in Dermatology}",
    journal = {JAMA Dermatology},
    volume = {154},
    number = {11},
    pages = {1247-1248},
    year = {2018},
    month = {11},
    abstract = "{Machine learning (ML), a form of artificial intelligence using computer algorithms, is often applied in ways we take for granted: Spotify to predict music that people may enjoy, Facebook to suggest friends to tag in photos, and Amazon to identify products to buy. Aside from these quotidian tasks, ML holds the promise of enhancing the delivery of quality health care. Recently, ML has been used to create programs capable of distinguishing between images of benign and malignant moles with accuracy similar to that of board-certified dermatologists. This technology could greatly assist dermatologists in diagnosing and treating skin diseases, thereby improving patient care. However, if not developed with inclusivity in mind, ML could exacerbate health care disparities in dermatology.}",
    issn = {2168-6068},
    doi = {10.1001/jamadermatol.2018.2348},
    url = {https://doi.org/10.1001/jamadermatol.2018.2348},
    eprint = {https://jamanetwork.com/journals/jamadermatology/articlepdf/2688587/jamadermatology\_adamson\_2018\_vp\_180011.pdf},
}

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  pages={8188--8197},
  year={2020}
}

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  year={2019},
  volume={abs/1908.09635}
}

@inproceedings{kearns2018preventing,
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  pages={2564--2572},
  year={2018}
}